---
base_model: intfloat/multilingual-e5-base
license: mit
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: multilingual-e5-base_censor_v0.1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# multilingual-e5-base_censor_v0.1

This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5077
- Accuracy: 0.7695
- Precision: 0.7729
- Recall: 0.7695
- F1: 0.7708
- Roc Auc: 0.8424
- Per Class F1: [0.8104358705451601, 0.7061407261629732]

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc | Per Class F1                             |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|:----------------------------------------:|
| 0.5485        | 1.0   | 2795 | 0.5249          | 0.7349   | 0.7498    | 0.7349 | 0.7383 | 0.8169  | [0.7723692804179954, 0.6827648980028912] |
| 0.4871        | 2.0   | 5590 | 0.5059          | 0.7610   | 0.7667    | 0.7610 | 0.7629 | 0.8362  | [0.8013980033834657, 0.7000926419808541] |
| 0.4392        | 3.0   | 8385 | 0.5077          | 0.7695   | 0.7729    | 0.7695 | 0.7708 | 0.8424  | [0.8104358705451601, 0.7061407261629732] |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1